1. Field of the Invention
The present invention relates to a method for inspecting on exterior of a semiconductor package, and more particularly, to a mark partitioning inspection method.
2. Description of the Background
The machine vision technology that has been developed in recent years is an important technology in automatic semiconductor package inspection. In the semiconductor package automatic inspection, the inspection items may be classified into two categories: electrical characteristic and function inspection; and exterior inspection, where the exterior inspection inspects whether semiconductor packages have any lead frame or mark defects.
In the exterior inspection, locations, directions, distortions, scratches, omissions, and breaks of various marks indicating semiconductor package information, such as product name and manufacturer name are inspected.
As semiconductor packages are gradually becoming smaller, lots of time and cost are required to process such inspection items using visual inspection, and distribution of defective products by misjudgment results in cost increase. Accordingly, high-performance inspection technologies have been recently developed in and applied to a field of semiconductor mark inspection.
Mark inspection algorithm largely includes image acquisition, image processing, feature extraction, object recognition and classification, and studies on method of effectively inspecting whether a mark is defective have been developed on the basis of character recognition, such as optical character recognition (OCR) and optical character verification (OCV).
For mark inspection of a semiconductor package, it should be considered to shorten inspection time through a simple and high-reliable algorithm. Furthermore, an OCV algorithm, in which certain characters to be inspected are known in advance and only the known characters are inspected, is more appropriate than an algorithm of OCR in which a lot of data are required for character recognition.
In OCV, defective marks are generally inspected using correlation coefficient, and location defect of marks is inspected through location data thereof.
Meanwhile, though strict inspection technology is required to find defects of a mark since such defects may exist in various types and locations, quite a few problems become known when defective marks are inspected using OCV.
Defective marks are typically generated by scratch error or mark printing error that has been made on the marks, and may come in various types, i.e., an edge portion of the mark being cut off, or a middle portion of mark being broken.
For a mark having a low level of defectiveness, there is a problem in that it is difficult to determine whether there is a defect on the mark using a normalized correlation coefficient method such that the defect cannot be detected.